Simple tools for forecasting waterflood performance

Abstract

Empirical and/or semianalytical tools are frequently applied in most waterflood operations, although grid-based models are also often used. This paper examines the performance of some commonly used tools, such as the water–oil ratio (WOR), Y-function, and Arps. Besides those tools, we introduce a semianalytical approach, which is a modified version of the Y-function formulation. Two other tools that have gained significant traction in unconventional-reservoir performance forecasting, the stretched-exponential decline model (SEDM) and the capacitance–resistance model (CRM) are also used here. Based on synthetic and field data, the results show that the Arps method is remarkably accurate in all flooding situations, regardless of the underlying physical mechanisms; other published data tend to support this notion. Similarly, both the SEDM and the proposed modified-Y-function method also yield solutions with good accuracy. The latter solutions tend to be pessimistic, however.